Full Report
The Importance of the Production Phase in
Vehicle Life Cycle GHG Emissions
Background
Historically, fuel economy regulations have been an effective mechanism for improving vehicle
fuel economy and reducing greenhouse gas (GHG) emissions associated with fuel combustion.
From 2004 to 2014, tailpipe CO2 emissions have decreased by 95 grams per mile (g/mi), or 21
percent, and overall average fuel economy has increased by 5.0 mpg, or 26 percent. 1 These
improvements were achieved primarily through the development and implementation of new
engine and transmission technologies. However, as regulations become even more stringent,
automakers are looking to additional solutions, such as reducing the mass of vehicles to
decrease fuel consumption, commonly referred to as “lightweighting.” A common strategy of
lightweighting is using materials which enable the weight reduction of various vehicle
components and systems, while still maintaining functionality. These materials may include
advanced high-strength steels (AHSS), aluminum, and in some cases carbon fiber composites or
magnesium. Each of these materials can contribute to vehicle lightweighting helping to improve
fuel economy; however, each does so at different manufacturing cost levels and environmental
impacts.
While the focus of federal regulations typically has been on the vehicle use phase (tailpipe
emissions), the true GHG profile of a vehicle is only evident by considering the entire life cycle.
A vehicle’s life cycle has three parts (or phases): production, use (driving) and end-of-life
(recycling and/or disposal).
The production phase can account for a significant portion of the overall life cycle emissions.
For the cases described in this paper, the production phase comprises nearly 20 percent of total
GHG emissions for internal combustion engine vehicles, and as much as 47 percent for battery
electric vehicles (BEVs). 2 Other sources have described even greater values for the ratio of
production emissions to total life cycle emissions. As overall fuel economy improves over time,
production emissions will become even more important. If alternate powertrain vehicles such as
BEVs increase in share, the importance of production emissions is increased even further. These
1 U.S. Environmental Protection Agency, Office of Transportation and Air Quality (OTAQ). “Light-Duty Automotive Technology,
Carbon Dioxide Emissions, and Fuel Economy Trends: 1975 – 2015” website. Available online:
http://www3.epa.gov/otaq/fetrends.htm.
2 Derived from the peer-reviewed University of California, Santa Barbara Automotive Materials GHG Comparison Model V4,
October 2013.
1
production emissions result in environmental impacts before a vehicle is ever driven and they
are not accounted for in current fuel economy regulations or factored into most automotive
design practices. Once emitted, GHGs immediately begin absorbing energy from the sun
leading to warming of the atmosphere. Major GHGs remain in the atmosphere for a range of
decades (CH4) to centuries (CO2) after being released. 3 Therefore, the timing of GHG emissions
is a critical consideration.
This paper will demonstrate the importance of considering production phase emissions in any
vehicle regulatory program that attempts to reduce overall GHG emissions from vehicles. The
University of California Santa Barbara Automotive Materials GHG Comparison Model V4
(UCSB Model) was used to model various automotive lightweight scenarios for this purpose.
The UCSB Model, initially developed in 2007 by Dr. Roland Geyer, calculates GHG emissions
and energy over the entire life cycle of a vehicle. It has been peer reviewed and has gone
through three update cycles since it was first developed. The model is fully transparent and
publicly available at http://www.worldautosteel.org/projects/vehicle-lca-study/automaterials-ghg-comparison-model/. The potential unintended consequences of a focus solely on
tailpipe emissions will be demonstrated through several approaches using the UCSB Model.
First, the default vehicles in the model (based on material composition, mass and fuel efficiency
representative of model year 2007 vehicles) will be compared to two lightweight contender
vehicles, one AHSS-intensive and the other aluminum-intensive. Then, the baseline vehicles
will be updated to reflect curb weights and fuel efficiencies of model year 2013 vehicles. Finally,
a scenario representative of a future vehicle will be modeled, when fuel efficiency requirements
(in compliance with CAFE regulations) will have improved and will be very similar within
identical vehicle footprints. The modeling and analyses reported herein will systematically lead
to the definitive conclusion: Any vehicle regulation must also consider material production
emissions to ensure a net overall reduction in GHG emissions to the environment.
GHG and Energy Footprinting using the UCSB Model
The UCSB Model compares a baseline vehicle to one or more contender vehicles, based on a
comprehensive set of input parameters. These parameters include, but are not limited to:
•
•
•
•
•
•
Lifetime driving distance
Material replacement coefficients
Secondary mass savings
Material production GHG emissions
Degree of powertrain optimization/fuel reduction values
Forming (stamping) yields
U.S. Environmental Protection Agency. “Climate Change Indicators in the United States: Greenhouse Gases” website. Available
online: http://www3.epa.gov/climatechange/science/indicators/ghg/
3
2
Most of the UCSB model scenarios included in this paper will consist of a baseline vehicle and
two contender vehicles, the contenders being an AHSS-intensive option and an aluminumintensive option. The contender vehicles are created within the UCSB Model by replacing the
steel body structure of the baseline vehicle with either AHSS or aluminum.
The UCSB Model was developed to represent global production of vehicles. Since the focus of
this paper is North American vehicle production and U.S. tailpipe emissions regulations,
several modifications were made to the default input parameters used in the model. Each of the
model scenarios described in the following sections will receive an alphanumeric designation,
and the Appendix will include a full list of the input parameters differing from the model’s
default values. The first five designations are MS1 (midsize sedan), SUV1 (SUV), TR1 (pickup
truck), HEV1 (hybrid electric vehicle) and BEV1 (battery electric vehicle). Occasionally, a single
parameter will be changed from one scenario to another. In these cases, the scenario designation
will include an additional letter, as in TR3a. The results of all scenarios modeled are
summarized in Table 1 (see page 10).
The first example is a simple model run (Scenario MS1), using the model’s default baseline midsize sedan, with input parameters representative of North American production as described in
the Appendix. After comparing an AHSS-intensive contender vehicle (C1) to an aluminumintensive option (C2), the results from this scenario are as follows:
Baseline
Contender 1 (C1): AHSS Body
Contender 2 (C2): Alum. Body
Difference C2-C1
% increase Alum. vs. AHSS
Scenario MS1 (kg CO2eq/vehicle)
Production
Use
End of Life
8,760
50,048
-2,218
8,260
48,284
-1,985
10,703
47,578
-3,217
2,444
-706
-1,232
29.6%
-1.5%
62.1%
Total
56,590
54,558
55,064
506
0.9%
In this simple case, the aluminum-intensive vehicle results in slightly higher (0.9 percent) life
cycle GHG emissions. However, the aluminum-intensive option results in nearly 30 percent
higher GHG emissions at the materials production phase. These emissions occur before the
vehicle is ever driven. It is also important to note these differences are for individual vehicle
comparisons. If the vehicles considered in this study were scaled to a production volume or
fleet of vehicles, these increases in emissions would be magnified significantly. For example,
converting the entire fleet of 2007 mid-size sedans in this case to aluminum-intensive vehicles
instead of AHSS would result in a net increase of 1.5 billion kg of GHG emissions.
Scenarios SUV1, TR1, HEV1 and BEV1 are similar to MS1, except the baseline and contender
vehicles are SUVs, pickups, HEVs or BEVs respectively. The results for these model runs are
very similar to MS1: the full life cycle emissions are higher in each case for the aluminumintensive vehicle, and these options exhibit significantly greater production phase emissions (31,
31, 30 and 19 percent greater respectively) versus the AHSS-intensive options. If the entire fleet
of 2007 SUVs and pickup trucks were converted to aluminum-intensive vehicles versus AHSS,
3
this would result in a net increase in GHG emissions of 1.5 billion kg and 1.4 billion kg
respectively.
Baseline
Contender 1 (C1): AHSS Body
Contender 2 (C2): Alum. Body
Difference C2-C1
% increase Alum. vs. AHSS
Scenario SUV1 (kg CO2eq/vehicle)
Production
Use
End of Life
11,217
70,191
-2,998
10,542
67,919
-2,684
13,841
67,010
-4,347
3,299
-909
-1,663
31.3%
-1.3%
62.0%
Total
78,410
75,777
76,504
727
1.0%
Baseline
Contender 1 (C1): AHSS Body
Contender 2 (C2): Alum. Body
Difference C2-C1
% increase Alum. vs. AHSS
Scenario TR1 (kg CO2eq/vehicle)
Production
Use
End of Life
10,708
81,154
-2,832
10,068
78,608
-2,534
13,193
77,589
-4,110
3,124
-1,019
-1,575
31.0%
-1.3%
62.2%
Total
89,030
86,141
86,672
531
0.6%
Baseline
Contender 1 (C1): AHSS Body
Contender 2 (C2): Alum. Body
Difference C2-C1
% increase Alum. vs. AHSS
Scenario HEV1 (kg CO2eq/vehicle)
Production
Use
End of Life
8,787
34,785
-2,232
8,287
33,509
-2,000
10,731
32,999
-3,232
2,444
-510
-1,232
29.5%
-1.5%
61.6%
Total
41,340
39,797
40,499
701
1.8%
Baseline
Contender 1 (C1): AHSS Body
Contender 2 (C2): Alum. Body
Difference C2-C1
% increase Alum. vs. AHSS
Scenario BEV1 (kg CO2eq/vehicle)
Production
Use
End of Life
11,365
18,047
-1,401
10,375
17,054
-1,191
12,358
16,657
-2,300
1,983
-397
-1,109
19.1%
-2.3%
93.1%
Total
28,011
26,237
26,714
477
1.8%
In addition to default parameters, the UCSB Model includes several default vehicles as baseline
vehicles, and the default sedan, SUV, etc. are used in the scenarios discussed above. However,
these baseline vehicles represent older vehicles (~2007) developed before CAFE regulations
were updated, and may not sufficiently represent the curb weight and fuel economy of presentday vehicles. As a next step, the UCSB Model is used to develop scenarios with more current
baseline vehicles and contender vehicles. This is accomplished by the following multi-step
process for each vehicle class (sedan, SUV, pick-up, HEV, and BEV):
1. Determine the production-weighted average vehicle mass for the top-selling vehicles in
the class, based on 2013 data;
4
2. Calculate the weight of the new body structure (material to be replaced by AHSS and
aluminum in the contender vehicles) by taking 25 percent of the curb weight, based on
default UCSB Model values; and,
3. Allow the model to calculate new fuel efficiency values based on the updated baseline
vehicle weights and any associated changes to the powertrain optimization parameter.
These updated vehicles were then used as baseline vehicles in the UCSB Model and updated
GHG scenarios were again calculated for AHSS-intensive and aluminum-intensive contender
vehicles. These scenarios are designated MS2, SUV2, TR2, HEV2 and BEV2. The results from the
updated mid-size sedan (MS2) scenario are shown below:
Baseline
Contender 1 (C1): AHSS Body
Contender 2 (C2): Alum. Body
Difference C2-C1
% increase Alum. vs. AHSS
Scenario MS2 (kg CO2eq/vehicle)
Production
Use
End of Life
8,066
47,723
-1,992
7,604
46,091
-1,777
9,864
45,439
-2,916
2,260
-653
-1,140
29.7%
-1.4%
64.2%
Total
53,798
51,919
52,386
468
0.9%
The results of MS1 and MS2 (above) are very similar. Additional results tables for models SUV2,
TR2, HEV2 and BEV2 can be found in the Appendix. All results for these updated baseline
vehicle scenarios (generally lighter curb weight and better fuel efficiency) are similar to the
corresponding results from scenarios using the default (older model) baseline vehicles. This
demonstrates the results are not significantly affected by the model year of the vehicles being
used as the baseline for comparison.
Incorporating Monte Carlo Analysis in the Results
A common criticism of the type of modeling described above is the results can be skewed in one
direction or another by selecting input parameters favorable to one material. While the
parameters used in the above modeling are credible and well-documented, this criticism has
been addressed by conducting several Monte Carlo simulations for an AHSS-intensive versus
aluminum-intensive vehicle comparison. In this context, the Monte Carlo approach involves
5,000 simulations of randomly selecting a value within a specified range of possible values for
each of several parameters and performing GHG calculations within the UCSB model. The
parameter ranges have been chosen to include all of the reasonable and credible values for each
variable. Included in this range of input parameters (listed in the Appendix) are some values
considered to be overly beneficial to alternative materials; however, they are included because
they have been suggested as credible by another materials trade association. Once the 5,000
iterations are complete, the results are displayed in a histogram showing the percentage of the
cases where one contender vehicle produces greater life cycle CO2 emissions versus the other
5
contender. By this approach, the entire range of credible parameter values can be assessed by
the model, thereby addressing the sensitivity of the parameters and reducing uncertainty.
Monte Carlo simulations were conducted for eight of the previously-described scenarios (midsize sedan, SUV, pickup truck, HEV), using the parameter ranges listed in the Appendix. (Note:
Because of the manner in which it calculates fuel efficiency, the model was unable to directly
develop a Monte Carlo simulation for battery electric vehicles.) These scenarios will be
designated MS1-MC, SUV1-MC, etc., and the resulting histograms for all eight cases are
included in the Appendix. The histogram for scenario MS2-MC is shown here as an example:
In this case, the AHSS-intensive mid-size sedan exhibits a lower life cycle GHG profile in nearly
70 percent of the Monte Carlo simulations, primarily as a result of its significantly lower
production-phase emissions. Simulation results for the eight scenarios demonstrate the AHSSintensive vehicle results in lower life cycle GHG emissions versus the aluminum-intensive
vehicle in a greater percentage of cases, across the entire range of parameter values even
including those considered outside the credible range. For most of the simulations, the AHSSintensive vehicle exhibited the lower total life cycle GHG emissions in about 70 percent of the
5,000 simulations. This approach clearly demonstrates the AHSS-intensive option is far more
likely to result in lower life cycle emissions even when a wide range of input parameters are
accommodated, and even though the AHSS-intensive option is calculated by the model to result
in slightly higher use-phase emissions.
6
Future (2025) Example Applying Real-World Automotive Design Practices
All of the previously described modeling relies on the data and formulas built into the UCSB
Model for calculating the fuel efficiencies of baseline and contender vehicles. However, if this
life cycle thinking approach is projected to a typical model year 2025 vehicle, the modeling must
acknowledge the realities of CAFE regulations, in that all automakers are striving to meet very
difficult MPG targets through 2025. Since cars are designed many years in advance, engineers
are already designing to meet these specific future targets. As this design process moves
forward, it becomes clear the production phase GHG emissions will become even more
significant, since use-phase emissions within vehicle footprints will, by necessity, become
significantly lower and essentially equal. For this phase of the GHG modeling, the fuel
efficiencies of both contender vehicles (AHSS-intensive and aluminum-intensive) are set equal
to the CAFE standard targets for the modeled vehicle, and thus the use-phase emissions are
equal. This scenario is based on the fact automakers are designing vehicles to meet, not exceed,
regulatory targets. Automakers will be challenged to meet CAFE-required minimum MPG
within each vehicle footprint and will be unlikely to invest the additional funds necessary to
take fuel efficiency beyond the required minimums. Increasing a vehicle’s fuel economy
requires monetary investments whether via materials, new engine and transmission
technologies, improved aerodynamic design, or other means. The cost of vehicles will increase
to meet fuel economy targets and there is no evidence consumers will accept any additional
costs to exceed these targets, especially when the cost of fuel is at a seven-year low and is
expected to remain low for many years.
The following scenario provides an example of this approach. For this model run, designated
TR3, the baseline vehicle was modeled after the curb weight and material composition of an
actual 2014 model year pickup truck, and the use-phase emissions were set equal for the two
contender vehicles. The primary aluminum ingot GHG profile, aluminum sheet recycled
content, and end-of-life recycling rates for steel and aluminum were also updated to reflect
future conditions, as described in the Appendix. All other parameters were the same as in
previous scenarios. The results from this assessment show an even greater life cycle GHG
penalty for the use of high-production-emissions materials:
Baseline
Contender 1 (C1): AHSS Body
Contender 2 (C2): Alum. Body
Difference C2-C1
% increase Alum. vs. AHSS
Scenario TR3 (kg CO2eq/vehicle)
Production
Use
End of Life
13,700
90,393
-4,174
13,199
62,953
-3,915
18,386
62,955
-7,274
5,188
3
-3,359
39.3%
0.0%
85.8%
Total
99,920
72,237
74,068
1,831
2.5%
In this example, since the use phase emissions are equal, the differences in the two contenders
arise only from the production and end-of-life phases. The aluminum-intensive option results in
39 percent higher production phase GHG emissions and 2.5 percent higher life cycle emissions
7
when the end-of-life phase is included. These differences are substantial, and it is again
important to note the production phase emissions occur before the vehicles are ever driven.
All scenarios to this point have been based on the use of the “avoided burden” method of
treating end-of-life recycling of vehicle materials. This is a complex subject that will not be
discussed in detail here, except to state this approach is more favorable to products with higher
production phase emissions. An alternate approach to end-of-life recycling, supported by many
practitioners, is the so-called “cut-off” methodology. As a form of sensitivity analysis, an
additional model run was conducted for the above-described 2025 scenario, whereby the cut-off
approach was used in lieu of the avoided burden approach for treatment of recycling. The
results of this run (designated TR3a) are reproduced below:
Baseline
Contender 1 (C1): AHSS Body
Contender 2 (C2): Alum. Body
Difference C2-C1
% increase Alum. vs. AHSS
Scenario TR3a (kg CO2eq/vehicle)
Production
Use
End of Life
13,182
90,393
0
12,735
62,953
0
17,866
62,955
0
5,131
3
0
40.3%
0.0%
Total
103,575
75,688
80,821
5,133
6.8%
As can be seen, these results show an even more dramatic difference between the two contender
vehicles. Over the full life cycle, the aluminum-intensive vehicle results in nearly 7 percent
higher GHG emissions versus the AHSS-intensive option and in the production phase, the
aluminum-intensive vehicle is responsible for over 40 percent higher GHG emissions.
Consideration of Time-Weighting of GHG Emissions
As mentioned previously, the production phase GHG emissions occur before the designated
vehicle is ever driven, and these emissions can have an even greater effect on global climate
change than emissions which occur later in the life cycle. Several academics and researchers
have identified the importance of “time-weighting” or discounting GHG emissions based on
whether they are produced today, or at some time in the future. For example, Kendall and
Price 4 state: “Accounting for emissions timing will unambiguously increase the contribution of nonuse
phase emissions to life cycle emissions intensity estimates.” This paper will not attempt to quantify
the effect of emissions timing, other than to point out any consideration of emissions timing
would tend to further increase the impact of production phase emissions, and would thereby
increase the overall life cycle impacts for materials such as aluminum with high-productionphase GHG emissions.
Kendall, Alissa and Price, Lindsay, Incorporating Time-Corrected Life Cycle Greenhouse Gas Emissions in Vehicle
Regulations, Environmental Science and Technology, 2012, 46 (5), pp. 2557-2563.
4
8
Summary
As automakers move to lightweighting as a significant component of their strategy to meet
increasingly stringent CAFE regulations, it becomes critically important to look beyond the
tailpipe, and instead consider the full life cycle emissions of vehicles. This paper has shown the
use of aluminum-intensive vehicles for lightweighting can result in higher life cycle GHG
emissions of 0.6 percent to nearly 7 percent, and higher production-phase GHG emissions of 19
percent to over 40 percent. When scaled to an entire annual fleet of sedans, SUVs or pickup
trucks, the conversion to an aluminum-intensive option versus AHSS results in a net increase in
GHG emissions of about 1.5 billion kg for each vehicle class.
The concept is not unlike what has happened in the construction industry over the last several
years. Initially, the focus of green building standards and rating programs was on operational
energy improvement, as it was the dominant phase in the life cycle of buildings. However, as a
building’s use phase has become increasingly more efficient, the focus is now shifting to
building materials and the construction process through the incorporation of new assessment
methods, including whole building life cycle assessment and environmental footprinting of
building products. Similarly in automotive design, regulators and engineers have been doing an
excellent job improving use-phase fuel economy, but now need to consider the emissions from
production of the materials that comprise every vehicle, in order to lessen the automotive
sector’s overall impact on our environment with certainty. Since automakers will likely use
some high production-phase emissions materials as part of their strategy to meet CAFE
regulations, these emissions must be accounted for in any regulation, to avoid the unintended
consequence of actually increasing overall GHG emissions.
9
Table 1 - Summary of Modeled Scenarios
10
APPENDIX
Detailed Results from All Tested Scenarios
Baseline
Contender 1 (C1): AHSS Body
Contender 2 (C2): Alum. Body
Difference C2-C1
% increase Alum. vs. AHSS
Scenario MS1 (kg CO2eq/vehicle)
Production
Use
End of Life
8,760
50,048
-2,218
8,260
48,284
-1,985
10,703
47,578
-3,217
2,444
-706
-1,232
29.6%
-1.5%
62.1%
Total
56,590
54,558
55,064
506
0.9%
Baseline
Contender 1 (C1): AHSS Body
Contender 2 (C2): Alum. Body
Difference C2-C1
% increase Alum. vs. AHSS
Scenario SUV1 (kg CO2eq/vehicle)
Production
Use
End of Life
11,217
70,191
-2,998
10,542
67,919
-2,684
13,841
67,010
-4,347
3,299
-909
-1,663
31.3%
-1.3%
62.0%
Total
78,410
75,777
76,504
727
1.0%
Baseline
Contender 1 (C1): AHSS Body
Contender 2 (C2): Alum. Body
Difference C2-C1
% increase Alum. vs. AHSS
Scenario TR1 (kg CO2eq/vehicle)
Production
Use
End of Life
10,708
81,154
-2,832
10,068
78,608
-2,534
13,193
77,589
-4,110
3,124
-1,019
-1,575
31.0%
-1.3%
62.2%
Total
89,030
86,141
86,672
531
0.6%
Baseline
Contender 1 (C1): AHSS Body
Contender 2 (C2): Alum. Body
Difference C2-C1
% increase Alum. vs. AHSS
Scenario HEV1 (kg CO2eq/vehicle)
Production
Use
End of Life
8,787
34,785
-2,232
8,287
33,509
-2,000
10,731
32,999
-3,232
2,444
-510
-1,232
29.5%
-1.5%
61.6%
Total
41,340
39,797
40,499
701
1.8%
11
Baseline
Contender 1 (C1): AHSS Body
Contender 2 (C2): Alum. Body
Difference C2-C1
% increase Alum. vs. AHSS
Baseline
Contender 1 (C1): AHSS Body
Contender 2 (C2): Alum. Body
Difference C2-C1
% increase Alum. vs. AHSS
Scenario BEV1 (kg CO2eq/vehicle)
Production
Use
End of Life
11,365
18,047
-1,401
10,375
17,054
-1,191
12,358
16,657
-2,300
1,983
-397
-1,109
19.1%
-2.3%
93.1%
Scenario MS2 (kg CO2eq/vehicle)
Production
Use
End of Life
8,066
47,723
-1,992
7,604
46,091
-1,777
9,864
45,439
-2,916
2,260
-653
-1,140
29.7%
-1.4%
64.2%
Total
28,011
26,237
26,714
477
1.8%
Total
53,798
51,919
52,386
468
0.9%
Baseline
Contender 1 (C1): AHSS Body
Contender 2 (C2): Alum. Body
Difference C2-C1
% increase Alum. vs. AHSS
Scenario SUV2 (kg CO2eq/vehicle)
Production
Use
End of Life
9,094
63,404
-2,306
8,559
61,603
-2,057
11,174
60,883
-3,375
2,615
-720
-1,318
30.5%
-1.2%
64.1%
Total
70,192
68,106
68,682
576
0.8%
Baseline
Contender 1 (C1): AHSS Body
Contender 2 (C2): Alum. Body
Difference C2-C1
% increase Alum. vs. AHSS
Scenario TR2 (kg CO2eq/vehicle)
Production
Use
End of Life
10,853
81,705
-2,879
10,193
79,076
-2,572
13,419
78,024
-4,199
3,226
-1,052
-1,626
31.6%
-1.3%
63.2%
Total
89,679
86,697
87,245
548
0.6%
Baseline
Contender 1 (C1): AHSS Body
Contender 2 (C2): Alum. Body
Difference C2-C1
% increase Alum. vs. AHSS
Scenario HEV2 (kg CO2eq/vehicle)
Production
Use
End of Life
7,822
32,447
-1,918
7,379
31,315
-1,711
9,547
30,862
-2,805
2,169
-453
-1,094
29.4%
-1.4%
63.9%
Total
38,351
36,983
37,605
622
1.7%
12
Scenario BEV2 (kg CO2eq/vehicle)
Total
Use
End of Life
Production
29,944
-1,562
12,423
19,083
-1,347
28,126
11,408
18,065
28,615
-2,484
17,658
13,441
489
-1,137
2,033
-407
1.7%
84.4%
-2.3%
17.8%
Baseline
Contender 1 (C1): AHSS Body
Contender 2 (C2): Alum. Body
Difference C2-C1
% increase Alum. vs. AHSS
Baseline
Contender 1 (C1): AHSS Body
Contender 2 (C2): Alum. Body
Difference C2-C1
% increase Alum. vs. AHSS
Scenario TR3 (kg CO2eq/vehicle)
Production
Use
End of Life
13,700
90,393
-4,174
13,199
62,953
-3,915
18,386
62,955
-7,274
5,188
3
-3,359
39.3%
0.0%
85.8%
Total
99,920
72,237
74,068
1,831
2.5%
Baseline
Contender 1 (C1): AHSS Body
Contender 2 (C2): Alum. Body
Difference C2-C1
% increase Alum. vs. AHSS
Scenario TR3a (kg CO2eq/vehicle)
Production
Use
End of Life
13,182
90,393
0
12,735
62,953
0
17,866
62,955
0
5,131
3
0
40.3%
0.0%
Total
103,575
75,688
80,821
5,133
6.8%
Baseline
Contender 1 (C1): AHSS Body
Contender 2 (C2): Alum. Body
Difference C2-C1
% increase Alum. vs. AHSS
Scenario TR3b (kg CO2eq/vehicle)
Production
Use
End of Life
13,681
90,393
-4,174
13,179
62,953
-3,915
18,176
62,955
-7,274
4,997
3
-3,359
37.9%
0.0%
85.8%
13
Total
99,900
72,217
73,858
1,640
2.3%
Monte Carlo Simulation Results
UCSB Model Mid-Size Sedan, Default Baseline (MS1) Monte Carlo
Relative Results Frequency Data
Select Comparison:
Lower Emissions for Aluminumintensive Option (30.6% )
Lower Emissions for AHSSintensive Option (69.4% )
(6,000)
(5,500)
(5,000)
(4,500)
(4,000)
(3,500)
(3,000)
(2,500)
(2,000)
(1,500)
(1,000)
(500)
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
5,000
5,500
6,000
UCSB Model Mid-Size Sedan, Updated Baseline (MS2) Monte Carlo
Relative Results Frequency Data
Select Comparison:
Lower Emissions for Aluminumintensive Option (31.1% )
Lower Emissions for AHSSintensive Option (68.9% )
14
(6,000)
(5,500)
(5,000)
(4,500)
(4,000)
(3,500)
(3,000)
(2,500)
(2,000)
(1,500)
(1,000)
(500)
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
5,000
5,500
6,000
UCSB Model SUV, Default Baseline (SUV1) Monte Carlo
Relative Results Frequency Data
Select Comparison:
Lower Emissions for Aluminumintensive Option (28.3% )
Lower Emissions for AHSSintensive Option (71.7% )
(6,000)
(5,500)
(5,000)
(4,500)
(4,000)
(3,500)
(3,000)
(2,500)
(2,000)
(1,500)
(1,000)
(500)
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
5,000
5,500
6,000
UCSB Model SUV, Updated Baseline (SUV2) Monte Carlo
Relative Results Frequency Data
Select Comparison:
Lower Emissions for Aluminumintensive Option (29.1% )
Lower Emissions for AHSSintensive Option (70.9% )
15
(6,000)
(5,500)
(5,000)
(4,500)
(4,000)
(3,500)
(3,000)
(2,500)
(2,000)
(1,500)
(1,000)
(500)
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
5,000
5,500
6,000
UCSB Model Pick-up Truck, Default Baseline (TR1) Monte Carlo
Relative Results Frequency Data
Select Comparison:
(6,000)
(5,500)
(5,000)
Lower Emissions for Aluminumintensive Option (39.4% )
Lower Emissions for AHSSintensive Option (60.6% )
(4,500)
(4,000)
(3,500)
(3,000)
(2,500)
(2,000)
(1,500)
(1,000)
(500)
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
5,000
5,500
6,000
UCSB Model Pick-up Truck, Updated Baseline (TR2) Monte Carlo
Relative Results Frequency Data
Select Comparison:
(6,000)
(5,500)
(5,000)
Lower Emissions for Aluminumintensive Option (40.1% )
Lower Emissions for AHSSintensive Option (59.9% )
(4,500)
(4,000)
(3,500)
(3,000)
(2,500)
(2,000)
(1,500)
(1,000)
(500)
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
5,000
5,500
6,000
16
UCSB Model Hybrid Electric Vehicle, Default Baseline (HEV1) Monte Carlo
Relative Results Frequency Data
Lower Emissions for AHSSintensive Option (69.0% )
Select Comparison:
Lower Emissions for Aluminumintensive Option (31.0% )
(6,000)
(5,500)
(5,000)
(4,500)
(4,000)
(3,500)
(3,000)
(2,500)
(2,000)
(1,500)
(1,000)
(500)
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
5,000
5,500
6,000
UCSB Model Hybrid Electric Vehicle, Updated Baseline (HEV2) Monte Carlo
Relative Results Frequency Data
Lower Emissions for AHSSintensive Option (68.9% )
Select Comparison:
Lower Emissions for Aluminumintensive Option (31.1% )
17
(6,000)
(5,500)
(5,000)
(4,500)
(4,000)
(3,500)
(3,000)
(2,500)
(2,000)
(1,500)
(1,000)
(500)
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
5,000
5,500
6,000
Description of Select UCSB Model Input Parameters
Lifetime Driving Distance (LTDD). The total number of miles a vehicle can be expected to be driven
during its useful lifetime. A 2006 study by the National Highway Traffic Safety Administration (NHTSA)
reports lifetime mileage for passenger cars (152,137 miles) and light-duty trucks (179,954 miles). Over
time, the average miles driven per year in the U.S. has declined; however, vehicle lifetimes are increasing.
Secondary Mass Change (SMC) or Secondary Mass Savings. Additional vehicle mass that can be saved,
for example in braking and suspension systems, as a result of the reduction in mass due to primary
lightweighting. Typically expressed as a percentage of primary mass savings.
Material Replacement Coefficient (MRC). The ratio of substituting one material for another. For example,
the MRC for advanced high strength steel (AHSS) is 0.75 lbs AHSS/lb mild steel. This means, by
switching from mild steel to AHSS in a given component-level application, 25 percent less steel by weight
is needed.
Forming Yield. The percentage of material carried through to a finished automotive part during the
stamping or forming process. The inverse is the amount of prompt scrap generated. For example, a 55
percent forming yield for steel means that for every ton of steel entering the stamping process, 0.55 tons
becomes an automotive part used in the vehicle and 0.45 tons of steel scrap is collected for recycling.
End-of-life (EOL) Recycling Rate. The amount of a given material in a vehicle that will ultimately be
recycled into new products once the vehicle reaches the end of its useful life. The EOL Recycling Rate is
the product of three separate rates: vehicle collection efficiency, automotive shredder efficiency, and
material recovery following shredding.
Alpha. Used in recycling allocation methodology, alpha provides an indication of the effect scrap, such as
steel or aluminum scrap, generation has on the collection of scrap in a given system. When alpha is set at
0, which approximates the avoided burden methodology, all scrap generated from the system is collected
and used to displace primary material production in the next product life cycle. A credit is applied to the
net scrap leaving the system indicating the avoided burdens in the next life cycle. When alpha is set at 1,
the cut-off method is approximated, which assigns no credits or burdens to scrap entering or leaving the
product system.
Primary Aluminum Ingot Production Emissions. Aluminum ingots are produced via primary (smelterbased) or secondary (recycling) processes. Both processes are encapsulated by the UCSB model. The vast
majority, if not all, of the secondary ingot production occurs in North America. Currently, 80 percent of
the primary aluminum ingots used in North America are produced in North America, with the remaining
20 percent imported from other regions. According to the Aluminum Association, primary ingot
produced in North America, has cradle-to-gate greenhouse gas (GHG) emissions of 8.937 ton CO2eq/ton
ingot. According to aluminum industry power accounting, 75 percent of the ingots are produced using
electricity generated by hydropower. The validity of this assumption is not well documented, but was
used in the modeling described in this paper. Primary ingots imported into the U.S. were modeled with
cradle-to-gate GHG emissions of 16.5 ton CO2eq/ton ingot from the International Aluminum Institute’s
“Global including China” primary ingot data, which includes a global average mix of fossil and
18
renewable energy sources. The representative GHG emissions intensity for North America was calculated
as 10.4 ton CO2eq/ton ingot by taking the percentage split of North American vs. imported ingots, and is
believed to be a conservative estimate.
Steel Production Emissions. The default UCSB model values for GHG intensities of steel production were
used in this study. There is sufficient capacity in North America to supply automotive steels for North
American vehicle production. The use of imported steel in automotive applications is very limited.
Furthermore, the emissions profile of steel production does not vary widely from region to region (with a
few exceptions that are not applicable to this study).
Primary Aluminum Ingot Production Energy. A calculation method was applied consistent with the
approach to primary aluminum ingot production emissions described above.
Fuel Reduction Value (FRV) and Powertrain Resizing. This value indicates the amount of liquid fuel that
is saved for a given amount of mass savings and is expressed in units of “liters/100km*100kg”. The UCSB
model includes data for different vehicle classes and powertrain types as derived from engine map
simulations by Forschungsgesellschaft Kraftfahrwesen (fka). Different FRVs are incorporated into the
model to approximate full powertrain resizing as a result of vehicle lightweighting and to represent no
associated resizing of the powertrain. Full powertrain resizing assumes a fully optimized engine design
which is not demonstrated in practice. A given power train is often used in several vehicle models and
many vehicle models are offered with different powertrain options. Therefore, a conservative
approximation of 50 percent powertrain resizing, which assigns 50 percent of the benefits of fully
optimized powertrain resizing, was selected for the modeling described in this paper.
19
Table 2 - UCSB Model Input Parameters
(Note: UCSB default values are used for parameters not listed in this table.)
Parameter
Unit
Possible Range
Low
High
Proposed
Value
(2013)
Lifetime Driving
Distance (LTDD) passenger car
km
200,000
300,000
245,000
miles
124,224
186,335
152,174
LTDD - light-duty
trucks
km
250,000
350,000
290,000
miles
155,280
217,391
180,124
Secondary Mass
Change
% of primary
mass savings
5%
25%
20%
Material
Replacement
Coefficient (MRC) –
AHSS
lb AHSS/
lb steel
0.7
0.86
0.75
MRC – Aluminum
lb Alum./
lb steel
0.6
0.7
0.65
Recycled Content Rolled/Extruded
Aluminum
% secondary
production
0%
50%
38%
Forming Yield Rolled Aluminum
%
45%
55%
50%
20
Justification for Proposed
Values
NHTSA 2006 study
indicates 152,137 lifetime
mileage (244,941 km)
NHTSA 2006 study
indicates 179,954 lifetime
mileage (289,726 km)
Design Advisor - Don
Malen and FKA
whitepaper, Jan. 2013; 25%
for fully optimized vehicle
Don Malen SAE paper on
MRC; steels continually
advancing - lighter,
stronger; A2Mac1 does not
capture advances in AHSS
Mass reduction
benchmarking (A2Mac1);
0.6 realized by aluminum
replacing mild steel
initially, but not sustaining
as vehicle designs advance
Accenture N. American
Smelter Study indicates
38% secondary production
in 2014 nationally. 67.5%
recycled content reported
in Aluminum Association
2013 LCA report as
estimate for avg. rolled
aluminum products (not
automotive specific).
Auto LCA Technical Team;
flat steel @ 55% in UCSB
Model default; aluminum
blanks are larger than
steel, thereby more scrap
generated from stamping
Forming Yield Extruded/Cast Al.
%
80%
80%
80%
Forming Yield - Flat
Carbon Steel and
AHSS
EOL Recycling Rate –
Steel
%
50%
60%
55%
%
90%
95%
90%
EOL Recycling Rate –
Aluminum
%
79%
95%
79%
Alpha
-
0
1
0.1
Primary Aluminum
Ingot Source
Location
Aluminum primary
ingot production
emissions - NA
% N.A
42%
80%
80%
ton CO2eq/ton
8.937
11.3
8.94
Aluminum primary
ingot production
ton emissions Imported
CO2eq/ton
10.5
20+
16.5
Primary Aluminum
ingot production
emissions BLENDED
Aluminum primary
ingot production
TOTAL energy - NA
Aluminum primary
ingot production
FOSSIL energy - NA
Aluminum primary
ingot production
TOTAL energy Imported
ton CO2eq/ton
--
--
10.4
MJ/kg
--
--
138
MJ/kg
--
--
73.4
MJ/kg
--
--
187
Aluminum primary
ingot production
FOSSIL energy Imported
MJ/kg
--
--
160
% Imported
20%
21
Auto LCA Technical Team;
UCSB Model default value;
alignment with Al.
industry
Auto LCA Technical Team;
aligned with UCSB Model
default values
Auto LCA Technical Team;
UCSB Model default
values
Auto LCA Technical Team;
UCSB Model default
values
0 indicates full avoided
burden approach;
sensitivity will test the
50/50 method and cut-off
approach
Accenture N. American
Smelter Study
Aluminum Association
2013 LCA Report for
primary ingot produced in
N.A.
“Global including China”
average primary
aluminum, which includes
mix of fossil and
renewable sources.
Incorporates percentage of
domestic vs. imported
production
Net calorific value (LHV);
Aluminum Association
2013 LCA Report
Net calorific value (LHV);
Aluminum Association
2013 LCA Report
Net calorific value (LHV);
Global including China
average, which includes a
mix of fossil and
renewable sources.
Net calorific value (LHV);
Global including China
average, which includes a
mix of fossil and
renewable sources.
Primary Aluminum
ingot production
TOTAL energy BLENDED
Primary Aluminum
ingot production
FOSSIL energy BLENDED
Aluminum
secondary ingot
production emissions
MJ/kg
--
--
148
Incorporates percentage of
domestic vs. imported
production
MJ/kg
--
--
90.7
Incorporates percentage of
domestic vs. imported
production
ton CO2eq/ton
--
--
1.2
Aluminum
secondary ingot
production TOTAL
energy
Aluminum
secondary ingot
production FOSSIL
energy
Powertrain Re-sizing
MJ/kg
--
--
19.7
MJ/kg
--
--
15.7
% of
powertrain
resizing benefit
0%
[no
resizing]
100%
[full
resizing
benefit]
50%
Fuel Reduction Value
(FRV):
Compact
Mid-size
SUV
l/100km*100kg
0.112
0.094
0.107
0.252
0.325
0.293
0.182
0.210
0.200
Aluminum Association
2013 LCA Report for
secondary ingot produced
in N.A.
Aluminum Association
2013 LCA Report for
secondary ingot produced
in N.A.
Aluminum Association
2013 LCA Report for
secondary ingot produced
in N.A.
Full powertrain resizing
assumes fully optimized
engine design which is not
demonstrated. OEMs use a
given power train in
several models and vehicle
models often offered with
different powertrain
options.
Data from fka engine map
simulations. Low value
represents no powertrain
resizing; high value
represents full powertrain
resizing. Proposed value
represents percentage of
powertrain resizing
indicated above.
22
Future (2025) Illustrative Example
In these scenarios (TR3, TR3a, and TR3b), a theoretical 2025 case was modeled in which the vehicle
composition is updated to represent a current pick-up truck and several parameters were updated to
reflect 2025 conditions. The baseline vehicle composition is based on a Model Year 2014 pick-up truck
with the two contenders representing an AHSS-intensive and an aluminum-intensive version. In
addition, the fuel economy is set at 30.6 MPG for both contender vehicles in the UCSB model, which is the
2025 CAFE target for the assessed vehicle footprint. This scenario is intended to illustrate the importance
of the production phase to the total vehicle life cycle as the efficiency of the use phase improves and
becomes very similar for vehicles in the same class. To reflect future conditions, three key variables were
changed from those represented in Table 2. All other parameters were held constant as a conservative
estimate or for lack of additional information.
First, the percentage of imported vs. North American produced primary aluminum ingots was increased
from 20 percent imported/80 percent North American to 58 percent imported/42 percent North
American based on the findings of an independent smelter study conducted by Accenture. To meet the
aluminum industry’s projected increase in demand of aluminum sheet for the North American
automotive sector, Accenture reports there will likely be a supply gap of at least 0.7 million metric tons in
2025. This revised percentage split was applied to the primary ingot production GHG intensity for North
American-produced ingots (8.937 ton CO2eq/ton ingot) and imported ingots (16.5 ton CO2eq/ton ingot)
to obtain a new weighted GHG emission factor of 13.3 ton CO2eq/ton ingot. Similarly, the percentage
split was applied to the North American and imported ingot production energy values (see Table 2) to
obtain new weighted energy consumption factors of 167 MJ/kg for total energy and 124 MJ/kg for fossil
energy.
The second key variable updated for this scenario was end-of-life (EOL) recycling rates. Assuming
recycling processes will continue to improve in the future, the EOL recycling rate for steel was increased
to 95 percent and to 90 percent for aluminum. Given the ease of magnetic separation and recovery for
steel, it is reasonable to assume at least a 5 percent difference between steel and aluminum recycling
rates. However, it is important to note this difference is not significant to the results in this or any other
scenario tested during the modeling described in this paper.
Third, the percentage of recycled content in automotive aluminum sheet was increased to 40% based on
the findings of the Accenture smelter study. In Scenario TR3b, the recycled content of aluminum sheet
was increased to 60 percent to assess the effect of this parameter on the study results. The aluminum
industry is researching methods for increasing the recycled content of automotive products for when
scrap of the necessary grade and quality becomes available in the future.
23
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